Latest AI and machine learning research in oncology/hematology for healthcare professionals.
Neoantigens are critical targets for cancer immunotherapy, yet the relationship between experimentally validated neoantigen burden and antigen processing machinery (APM) expression in determining clinical outcomes remains unclear. We mapped CEDAR-annotated neoantigens (CENs) onto mutation data from 43,980 patients across 14 cancer types using cBioPortal. APM gene expression was correlated with sur...
BACKGROUND AND AIMS: Hormone receptor-positive/human epidermal growth factor receptor 2-negative (HR+/HER2-) breast cancer (BC) accounts for the majority of BC cases. Although early-stage patients generally have favorable outcomes, recurrence and metastasis substantially worsen prognosis. We aimed to evaluate whether plasma metabolomics combined with machine learning could predict postoperative ou...
Transarterial chemoembolization (TACE) is a cornerstone locoregional therapy for hepatocellular carcinoma (HCC), yet most candidates also have cirrhos...
This paper introduces a deep learning-based framework for phase-only synthesis of cosecant-squared (csc²) radiation patterns in planar antenna arrays ...
OBJECTIVES: The need for a cost-effective, rapid, and increasingly accessible alternative to the 21-gene assay prompted this study, which developed a ...
The dynamics of tumor-immune interactions within a complex tumor microenvironment are typically modeled using a system of ordinary differential equati...
BACKGROUND: Gastric cancer (GC) remains a leading cause of cancer-related mortality worldwide, and the prognosis of advanced GC remains poor. Systemat...
BACKGROUND: Nasopharyngeal carcinoma (NPC) represents a highly prevalent and aggressive malignancy endemic to Southeast Asia. Early and accurate diagn...
Oral squamous cell carcinoma (OSCC) is often preceded by oral potentially malignant disorders (OPMDs). Despite this known association, the transition ...
The Ovarian-Adnexal Reporting and Data System (O-RADS), developed by the American College of Radiology (ACR), provides a standardized, evidence-based ...
Cancer is a complex and heterogeneous disease that is characterized by multi-level biological variability. Advances in high-throughput technologies ha...
OBJECTIVES: Early detection and resection of colorectal polyps prevent their progression toward advanced adenocarcinomas. The use of Texture and Color...
In recent years, the field of medical imaging has witnessed substantial progress due to the integration of advanced machine learning techniques, parti...
BACKGROUND: The clinical comorbidity of diabetes mellitus (DM) and gastric cancer (GC) presents a significant healthcare challenge, as these two condi...
INTRODUCTION: Exposure to ionizing radiation by endoscopy personnel during fluoroscopy-guided procedures remains a health hazard. We aimed to evaluate...
OBJECTIVES: Accurate prediction of axillary lymph node metastasis (ALNM) is crucial for tailoring breast cancer treatments, this study aimed to develo...
OBJECTIVE: To conduct an analysis of publication trends and a systematic review of randomized controlled trials (RCTs) to characterize the current sta...
BACKGROUND: Peripheral nerve sheath tumors (PNSTs) of the head and neck (H&N) show histopathological overlap. Although convolutional neural networks (...
PURPOSE: Accurate assessment of residual disease after neoadjuvant chemotherapy (NAC) is essential for surgical planning and prevention of incomplete ...
Multidrug resistance (MDR) remains the core clinical barrier limiting the achievement of durable and effective treatment for various tumors. With the ...